GMV is participating in CYBELE, an EU-funded project that aims to generate innovation and create value in the domain of agri-food by applying Precision Agriculture (PA) and Precision Livestock Farming (PLF) methods.

Right from the project kickoff GMV has been leading one of the nine demonstrators to weigh up and show the usefulness of PA and PLF technology, concentrating on the development of climate services for organic fruit production.

At the end of January the European platform HiPEAC hosted a workshop to present the prototype of the CYBELE platform. This prototype is fruit of the first 2 years of project development, combining HPC hardware and software, Big-Data and Cloud for running scalable data analyses.

GMV itself talked about the data-processing challenges involved in PA and PFA trials, plus solutions and optimizations in the implementation of field-scale yield data analysis using the CYBELE platform.

Working on this demonstrator, GMV has achieved notable headway in the conceptualization and exploration of machine-learning methods for forecasting frost and hail. These demonstrator trials were carried out in two zones of Valencia region.

Due to the sheer complexity of forecasting extreme-weather events, the trials were broken down into three blocks: hail forecasting, frost forecasting and the phenology of each type of fruit.

GMV’s work on this demonstrator draws on data from the Meteorological Archival and Retrieval System of the European Centre for Medium-Range Weather Forecasts (ECMWF) and the Spanish Meteorological Agency (Agencia Española de Meteorología: AEMET).